Unravelling three-dimensionally dynamics of spatial multi-modal data
Project description
Unravelling three-dimensionally dynamics of spatial multi-modal data with RidgeSpace
You can freely use RidgeSpace for illustrating, comparing, and tracking the spatial dynamics of molecular signals.
Overview of RidgeSpace.
Prerequisites
"matplotlib", "numpy", "pandas", "scipy"
Installation
I suggest that you can freely install RidgeSpace with pip.
pip install RidgeSpace
You can also use a separate conda environment for installing RidgeSpace.
conda create -y -n RidgeSpace_env python=3.7
source activate RidgeSpace_env
pip install RidgeSpace
Basic Examples
Examples of RidgeSpace.
Test data and code for RidgeSpace provided in the "tests" folder.
Single-gene spatial depiction:
RidgeSpace.pl_single(adata, plot_name = 'Mbp', obs_cluster='Clusters', elev=40, view=160))
Multi-modal spatial comparison:
RidgeSpace.pl_multipleOUT(adata, plot_nameA = 'Tnnt1', plot_nameB = 'Tnnt2', obs_cluster='Clusters', elev=20, view=160, plot_HE_bg=True)
Pseudotime spatial trajectory representation:
RidgeSpace.pl_trajectory(adata, plot_name = 'Pseudotime', obs_cluster='Clusters', elev=45, view=165, HE_z=10)
Further tutorials please refer to https://RidgeSpace.readthedocs.io/.
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